The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

This study investigates the potential of probabilistic classification to enhance credit-scoring accuracy, with a focus on model validation through reliability thresholds. By quantifying prediction ...